Overcoming Data Silos by Integrating AI Across Multiple Marketing Channels

Data Silo (n.) is a system, process, department, etc. that operates in isolation from others

Originally, a silo is a huge isolated storage container on a farm that stores grain. But the term has long funneled into the data science and marketing streams to mark an isolated activity or an incident that is not easily accessible by other larger components. 

Why do data silos occur?

Data silos occur when multiple departments, teams, or units work with their independent process. This creates a block in the overall function of any product, leading to a snag and delayed productivity output. It creates a block in accessing data that can prove useful to automate a process. 

How do data silos occur?

Data silos occur when there are incomplete, inefficient, and dysfunctional data sets in addition to a mismanagement of any process. This usually happens when there are too many cooks involved, resulting in an undercooked product. 

How to overcome data silos with AI?

One of the many perks of AI-backed processes is the seamless integration of multiple processes. With an AI-backed management automation tool, you can ensure a smooth workflow. Each step is carefully organized and arranged in a manner that enables you to access any data set easily. 

With GrowStack.ai, you can customize your workflow based on your needs and eliminate the problem of data silos. Different AI workflow tools offer different venues to explore and choose from. What makes GrowStack.ai different from most other options in the market is its model-agnostic offering. You can work your way around the tool to ensure that you are not left half-baked goods. Manage your data, streamline publishing, prepare calendars and timetables, get accurate data analysis, and more. Eliminate the possibility of any biases in your data set.